Description
1.Product analysis, quality and validation for Data Enrichment products; and
2.Data labeling and AI/model quality validation for Machine Learning capabilities.
The Product Analysts will move between these areas as business priorities require. They will help ensure that merchant and transaction data is accurately classified, product outputs meet expected quality standards, customer and operational feedback is translated into actionable insight, and product teams can make confident, data-informed decisions.
Responsibilities
•Product analysis, quality and validation for Data Enrichment products
•Data labeling and AI/model quality validation for Machine Learning capabilities
•Help ensure that merchant and transaction data is accurately classified
•Help ensure product outputs meet expected quality standards
•Translate customer and operational feedback into actionable insight
•Help product teams make confident, data-informed decisions
Requirements
•3+ years of relevant experience in a product analyst, data analyst, data quality, QA, product operations, data labeling, or similar role in a technology-driven environment
•Strong analytical and problem-solving skills, with exceptional attention to detail and consistency
•Comfortable working with data using tools such as SQL, spreadsheets, dashboards, or similar analytical tooling
•Experience working with large datasets, data-quality processes, testing, validation, or business-rule assessment
•Ability to investigate issues end-to-end, identify patterns and root causes, and communicate findings clearly
•Understanding of core machine-learning concepts and workflows, including the importance of high-quality training data and model validation
•Familiarity with classification problems and/or data annotation, labeling, or taxonomy-based workflows
•Strong written and verbal English communication skills
•Ability to collaborate effectively with both technical and non-technical stakeholders and to manage changing priorities
Nice to have
•Experience analysing transaction data, merchant data, categorisation systems, or other financial-data classification problems
•Experience with data labeling, annotation, model validation, or AI-assisted labeling workflows
•Familiarity with model-evaluation concepts and metrics, including precision, recall, F1 score, accuracy, and confusion matrices
•Experience supporting AI, machine-learning, MLOps, or data-platform environments
•Familiarity with Google Vertex AI or comparable machine-learning platforms
•Experience using SQL to investigate data issues and support product or quality analysis
•Experience with test planning, regression testing, migration validation, or release-quality activities
•Experience turning customer feedback or operational issues into structured analysis and product recommendations
Conditions
Not specified in the posting.
